Richard Gonzalez, PhD

richard gonzalez, phd

Dr. Gonzalez holds a Ph.D. in Psychology from Stanford University and a BA in Psychology from UCLA. He directs a new center, the Biosocial Methods Collaborative, at the University of Michigan on the development of methods for the integration of biological and social science data. In addition to his faculty positions at the University of Michigan at the Institute for Social Research, the Center for Human Growth and Development, Psychology and Marketing, he has been on the faculty of the University of Washington and a visiting professor at Princeton University.

Dr. Gonzalez’s main research areas are methodology and judgment/decision making. He develops mathematical models for psychological processes in decision making and has been exploring the role of emotions in decision making. He makes use of mathematical models that integrate multiple intra individual processes that span multiple levels of analysis from biological to psychological to cultural. His research in statistics has focused on nonparametric statistics, generalized linear (and nonlinear) mixed models, multivariate multilevel models, which include longitudinal designs, latent transition models and dyadic models, model-based classification methods such as latent class and mixture models, exploratory techniques such as classification and regression trees and machine learning classification techniques, and data visualization. Dr. Gonzalez works in both classical and Bayesian frameworks.